Oliver, N. and Kreger-Stickles, L., “PAPA: Physiology and Purpose-Aware Automatic Playlist Generation”, Proc. of ISMIR 2006, 7th Int. Conf on Music Information Retrieval, Victoria, Canada, 8-12 Oct. 2006, discloses an application that selects music to assist users in achieving specific exercising goals, and incorporates the user's physiological response to the music to determine the next song to play. Typically, the user is listening to music from his personal digital library (DML) by means of a portable digital music player. The system has access to the user's profile together with historic data in the form of logs of previous interactions with the system. The user also wears a set of physiological and environmental sensors. The user's DML is augmented with relevant metadata such as the song's tempo, average energy, duration, genre, etc. The system utilizes the user's bio-feedback and explicit feedback to learn a model of the set of features in the music—e.g. tempo, average energy, etc.—and the user's response to it.
A problem of the known system is that it can only work after it has accumulated data in its database, i.e. updated its model, preferably across the range of possible values of tempo, average energy, etc.